code: def test_spark_dataset_source_too_many_inputs(
      spark_session, tmp_path
  ):
      df = pd.DataFrame([[1, 2, 3], [1, 2, 3]], columns=["a", "b", "c"])
      df_spark = spark_session.createDataFrame(df)
      df_spark.write.mode("overwrite").saveAsTable(
          "temp", path=tmp_path
      )
  
      with pytest.raises(
          MlflowException,
          match='Must specify exactly one of "path", "table_name", or "sql"',
      ):
          SparkDatasetSource(path=tmp_path, table_name="temp")
  
file_path: mlflow/tests/data/test_spark_dataset_source.py
imports: import json
  import pandas
  import pytest
  from mlflow.data.dataset_source_registry import get_dataset_source_from_json
  from mlflow.data.spark_dataset_source import SparkDatasetSource
  from mlflow.exceptions import MlflowException
label_desc: Use image node_id 5 for calling a global function with example usage: test_spark_dataset_source_too_many_inputs(spark_session, tmp_path) without return types